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Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge., , , , and . MIDOG/MOOD/Learn2Reg@MICCAI, volume 13166 of Lecture Notes in Computer Science, page 147-152. Springer, (2021)Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans., , , and . Int. J. Comput. Assist. Radiol. Surg., 14 (11): 1901-1912 (2019)Variable Fraunhofer MEVIS RegLib Comprehensively Applied to Learn2Reg Challenge., , , , and . MICCAI (Challenges), volume 12587 of Lecture Notes in Computer Science, page 74-79. Springer, (2020)Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking., , , and . CoRR, (2018)Abstract: Deep Learning Based CT-CBCT Image Registration for Adaptive Radio Therapy., , , , , and . Bildverarbeitung für die Medizin, page 229. Springer, (2020)Deep-learning-based CT-CBCT image registration for adaptive radio therapy., , , , , and . Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 113130Q. SPIE, (2020)A system for fully automated monitoring of lesion evolution over time in multiple sclerosis., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11597 of SPIE Proceedings, SPIE, (2021)Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning., , , , , , , , , and 37 other author(s). CoRR, (2021)Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy., , , , , and . WBIR, volume 12120 of Lecture Notes in Computer Science, page 44-53. Springer, (2020)Fully automated longitudinal tracking and in-depth analysis of the entire tumor burden: unlocking the complexity., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)